Ant
colonies, bird flocks, rain forests, businesses, organizations, communities, the
stock market and the global economy all have something in common. They are
complex adaptive systems. Complex means composed of many parts
which are joined (literally "twisted") together. Adaptive refers to the fact that all living systems
dynamicallyadapt to their constantly changing environments as they strive to survive and
thrive. And systems means everything is interconnected and
interdependent.

"Complexity"
represents the middle area between static order at one end and chaos at the other. Thus
complexity is sometimes called the edge of chaos. If we think of static order as
ice and chaos as water vapor, complexity would be liquid water.

Using powerful computers, scientists from a wide range of fields – including
a number of Nobel Prize winners – have developed computer models that
simulate on the screen the evolution and changes that occur as complex adaptive
systems move, adapt, survive and thrive or – if their strategies are wrong –
die. These models have included customers making choices in retail stores,
investors trading in the stock market, baggage handling by airlines, product
distribution by major companies, and many other practical business applications.

These applications were not even possible until recently, when computers were
able to run complex mathematical programs or algorithms to simulate this
real-world activity. From these models and the analyses by the scientists who
create them have come a growing number of insights any organization can use
in the real world - without requiring any special computer programs or science.

Unlike nonadaptive complex systems, such as the weather, complex
adaptive systems have the ability to internalize information, to learn, and to
modify their behavior (evolve) as they adapt to changes in their environments.
In other words, they have brains. Examples of complex adaptive systems
include:

The patterns of
birds in flight

The interactions of varied life forms in an ecosystem

The
behavior of consumers in a retail environment

The rise and fall of species in evolution

The interactions of people and groups in a community

And other complex social, biological and ecological phenomena.

The findings of Complexity science can be used for more natural, more
productive, more enjoyable and far more innovative results managing people, organizations and
communities. This website is maintained by Lawrimore Communications Inc. to
share this exciting knowledge and promote its use for a better world.

Already leading-edge organizations ranging from global manufacturers and
service organizations to hospitals and advertising agencies are finding that the key principles of
Complexity science allow them to cope more effectively with rapid change and
make full use of human creativity. Many people believe this will become the
dominant form of organization in the 21st Century. Let us explain old
viewpoints and new science in a little more detail before getting into how
Complexity science can be used to develop an organization or community to higher
levels, especially in its most practical form, Codynamics.

Old Science And Our Views Of Reality

From the late-17th Century until the early 20th, the Laws of Motion and other
linear,
mechanical principles discovered by Isaac Newton dominated the understandings of
science and filtered down into every aspect of the Western world. This view of
reality over time penetrated our education system, our culture, our language,
our organizations and our management practices so completely that it became
taken for granted. Most people are not even conscious that they are using what
is called the mechanical view of reality when they think and talk. This view of
reality assumes:

Things happen because something causes them to happen (cause and effect).

We can understand what happened by reducing things to their components or
parts and examining those parts (reductionism).

The universe is orderly, follows natural laws, and works like an
incredibly complicated machine.

The best way to manage people is to organize them into a clear structure
and control them with clear directions.

The best results occur when work is streamlined to be as efficient as
possible, with a minimum of wasted effort, producing the most output in the
least amount of time (the "lean machine").

In the early 20th Century, the certainty of Newton's mechanics was undermined
by quantum mechanics and the Uncertainty Principle developed by Werner
Heisenberg. Albert Einstein found that time is relative, space is curved, matter
and energy are interchangeable, and many other new challenges to the old
Newtonian view of reality. So scientists began abandoning the Newtonian
worldview, while ordinary people held on to it.

Still for many years physics was considered the ultimate science and
mathematics the ultimate expression of reality. Scientists still practiced
reductionism, reducing things into their parts and examining the parts to
understand what made them tick. They reduced matter to quarks and gluons, and
they reduced life to DNA and the genetic code. Reductionism still works when you
are looking at inanimate objects or the genetic sources of life structure.

From around the 1950s on, leading biologists were taking a different tack. You can't
just reduce living organisms to machines, they believed. Living organisms are
very complicated. Even a single cell has more complexity than a typical
manufacturing plant. You can only understand living things as complex
systems. Viennese biologist Ludwig von Bertalanffy believed that all living
systems have certain characteristics in common, and his book "General System
Theory" paved the way for much of the work being done in Complexity today. To understand the
common characteristics of living
systems, click here.

The Shared Work of Nobel Prizewinners

The new science of Complexity evolved out of general systems theory
and a field of study known as
chaos
theory. James Gleick's "Chaos: Making A New Science" became a national
bestseller after its publication in 1987. The New York Times reporter
popularized such insights as the Butterfly Effect, whereby a butterfly flapping
its wings in India causes a series of air movements that eventually result in a
thunderstorm over Chicago. In the late 1980s a number of leading scientists were
discovering different aspects of order in chaos, using computer models which draw diagrams on
monitors, playing out mathematical algorithms at a speed impossible by hand. All
of this was very interesting, resulting in some fascinating images and insights.
But no one was quite sure how to use it other than improving weather
forecasting.

Then in the 1990s a group of brilliant scientists (including several Nobel
winners) affiliated with the Santa Fe Institute in New Mexico said, in effect,
"There's not much point in studying chaos. It's too chaotic. Let's study
Complexity, where with the help of computers we can actually figure something
out." And indeed they have discovered many things about "the real world" with
practical applications for business, management, community and economic development. They have discovered some
profound properties of life forms,
order and structure using
advanced computer modeling, which suggest powerful
new ways by which organizations can emerge, evolve and thrive in the increasingly
complex technological-economic environment. Or for that matter in your
community--wherever your organization operates.

Many are drawn to Complexity science because it
provides a more accurate view of reality. Others are attracted because
they have found through painful experience that traditional strategic planning is unsatisfactory because it does not
provide an effective way to manage people and tasks in an environment of constant change (complexity) on a day to day basis.
Codynamics is the most practical, useful application of Complexity science
available.

A very readable introduction to complexity science is available in Roger Lewin's
"Complexity: Life At The Edge of Chaos" (Chicago, 1992, 1999). The gaseous
molecules bouncing around in the room where you are right now are moving
chaotically, very randomly, with very little order. By contrast, "the science of
Complexity has to do with structure and order," Lewin writes (pg. 10), especially in
living systems such as social organizations, the development of the embryo,
patterns of evolution, ecosystems, business and nonprofit organizations, and their interactions with the
technological-economic environment.

"We're looking for the fundamental rules that underlie all these systems, not
just the details of any one of them," explains Chris Langton of the Santa Fe
Institute (pg. 11). "You can only understand complex systems using computers,
because they are highly nonlinear and are beyond standard mathematical
analysis." A linear equation such as x=2y can be graphed as a straight line. A
nonlinear equation produces a curve. Put several of them together and you have
complexity that only a computer can graph, yet still there is underlying
structure and order, as in real life.

"For three centuries science has successfully uncovered many of the workings
of the universe, armed with the mathematics of Newton and Leibniz," Lewin
continues (11). "It was essentially a clockwork world, one characterized by
repetition and predictability. The launching of a spacecraft to rendezvous with
the Moon after several days of travel depends on that (linear)
predictability.... Most of nature, however, is nonlinear and is not easily
predicted. Weather is the classic example...."

Complex Nonlinear Systems

In complex nonlinear systems (including the organization or community of which you are a
part):

1. "Small inputs can lead to dramatically large consequences," such as
the Butterfly Effect noted above. The recent attacks on New York and Washington
have also vividly shown how a relatively small "input," the actions of
two dozen terrorists, have dramatically altered the lives of an entire nation, and
much of the world, and further precipitated an economic recession as well as a new war.

2. "Very slight differences in initial conditions produce very different
outcomes." The next time the butterfly flaps its wings, nothing of
consequence happens. If the hijackers had all been overpowered by the passengers
and crew, and all the jets had all crashed in rural areas, as the
fourth one did, the outcomes would have been tragic but quite different

3. In complex dynamical systems, such as organizations or ecosystems,
"global properties flow from aggregate behavior of individuals. For an
ecosystem, the interaction of species within the community might confer a degree
of stability on it; for instance, a resistance to the ravages of a hurricane, or
invasion by an alien species. Stability in this context would be an emergent
property" (13). Likewise people interacting in an organization create a whole
that is greater than the sum of its parts, and the properties of the
organization emerge from their combined behavior. The interactions of
"companies, consumers and financial markets produces the modern capitalist
economy, 'as if guided by an invisible hand,' as the Scottish economist Adam
Smith once put it."

4. The scientists at Santa Fe Institute are especially interested in
types of nonlinear systems known as complex adaptive systems, as found in
living organisms and organizations. What makes a complex adaptive system
different from a nonadaptive complex system such as the weather is "a
compression of informationwith which it can predict the environment"
(15). In other words, learning! In the words of Institute member Murray
Gell-Mann, a genius Nobel prizewinner in physics who speaks 13 languages,
"Complex adaptive systems are pattern seekers. They interact with the
environment, 'learn' from the experience, and adapt as a result."

5. "Most complex systems exhibit what mathematicians call attractors,
states to which the system eventually settles, depending on the properties of
the system" (Lewin, 20). "Imagine floating in a rough and dangerous sea, one
swirling around rocks and inlets. Whirlpools become established, depending on
the topography of the seabed and the flow of water. Eventually, you will be
drawn into one of these vortexes. There you stay until some major perturbation,
or change in the flow of water, pushes you out, only to be sucked into another"
(20-21). Thus the existing structure of your organization is one attractor
state, but changes in the turbulent environment may cause it to change into
another type of structure altogether. If your organization resists too long, it
may become obsolete or extinct. If your organization learns how to learn, it can
adapt to the forces of change and go with the flow.

New Truth So Important For Leaders And Organizations

Now here is a profound truth so important for 21st
Century leaders and organizations: Most organizations today were established on
linear, mechanical principles, the organization as a machine, producing
goods and services. Science abandoned the mechanical view of the universe almost 100
years ago. Most of us are still operating on a worldview that is left over from
the machine age and is 100 years out
of date! This is the Information Age, and nonlinear, complex adaptive systems
are the best way to understand systems involving people.

"Managers are finding that many of their long-established business models are
inadequate to help them understand what is going on, or how to deal with it" (Lewin,
197). "Where managers once operated with a machine model of their world, which
was predicated on linear thinking, control and predictability, they now find
themselves struggling with something more organic and nonlinear, where limited
control and a restricted ability to predict are the norm."

The world is simply too complex
and fast-changing for linear models to work! But what is really exciting about
Complexity science is it provides a whole new way to "go with the flow" by
taking advantages of the discoveries of "rules" governing complex adaptive
systems. Here are some of those rules and an explanation of what they mean for
business and other organizations:

1. "The source of emergence is the interaction among agents who mutually
affect each other" (Lewin, pg. 202).Manager-leaders should focus on developing
relationships where people mutually affect each other, especially learning by
teams, for innovation and new adaptive structures to emerge. The best way to
facilitate this is through authentic dialogue, the
open exchange of thoughts and ideas which allow a team to function as a
super-human. This type of dialogue, common in older cultures such as American
Indians in colonial days, is "natural" but must be learned afresh by people who
are all too used to classrooms, committees, "meetings" and "discussions" where
there is usually a hidden or explicit agenda.

2. "Small changes can lead to large effects" (pg. 203). Managers
should lead change
through many small experiments, which adapt to the wide range of possibilities,
and find out which ones work best, then diffuse this change throughout the
organization. Let different teams try different adaptive experiments.

3. "Emergence (of order) is certain, but there is no certainty as to what
it will be. Create conditions for constructive emergence (of order) rather
than trying to plan a strategic goal in detail. Evolve solutions, don't design
them" (203). Detailed strategic planning simply does not work in today's
fast-changing world. Vision and goals are desirable, but let the strategies
emerge naturally. Don't try to figure it all out in advance.

4. "Greater diversity of agents in a system leads to richer emergent
patterns. Seek a diversity of people, their cultures, their expertise, their
ages, their personalities, their gender, so that when people interact in teams,
for example, creativity has the potential of being enhanced.... Specifically,
whatever enriches the interactions (that is relationships) among agents (that
is, people) in the system will lead to greater creativity and adaptability"
(203).